Package: QurvE 1.1.1

QurvE: Robust and User-Friendly Analysis of Growth and Fluorescence Curves

High-throughput analysis of growth curves and fluorescence data using three methods: linear regression, growth model fitting, and smooth spline fit. Analysis of dose-response relationships via smoothing splines or dose-response models. Complete data analysis workflows can be executed in a single step via user-friendly wrapper functions. The results of these workflows are summarized in detailed reports as well as intuitively navigable 'R' data containers. A 'shiny' application provides access to all features without requiring any programming knowledge. The package is described in further detail in Wirth et al. (2023) <doi:10.1038/s41596-023-00850-7>.

Authors:Nicolas T. Wirth [aut, cre, cph], Jonathan Funk [aut], Matthias Kahm [ctb], Maik Kschischo [ctb], Thomas Petzoldt [ctb], Andrew Stein [ctb], Michael W. Kearney [ctb], Santiago I. Hurtado [ctb], Mark Heckmann [ctb], Nicholas Hamilton [ctb], Evan Friedland [ctb], Heather Turner [ctb], Georgi N. Boshnakov [ctb]

QurvE_1.1.1.tar.gz
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QurvE.pdf |QurvE.html✨
QurvE/json (API)
NEWS

# Install 'QurvE' in R:
install.packages('QurvE', repos = c('https://nicwir.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nicwir/qurve/issues

On CRAN:

5.98 score 24 stars 6 scripts 219 downloads 64 exports 128 dependencies

Last updated 10 months agofrom:b2025dbbc1. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winNOTENov 02 2024
R-4.5-linuxNOTENov 02 2024
R-4.4-winOKNov 02 2024
R-4.4-macOKNov 02 2024
R-4.3-winOKNov 02 2024
R-4.3-macOKNov 02 2024

Exports:biosensor.eqexport_RDataexport_Tablefl.controlfl.drFitfl.drFitModelfl.reportfl.workflowflBootSplineflFitflFitLinearflFitSplinegrowth.controlgrowth.drBootSplinegrowth.drFitgrowth.drFitModelgrowth.drFitSplinegrowth.gcBootSplinegrowth.gcFitgrowth.gcFitLineargrowth.gcFitModelgrowth.gcFitSplinegrowth.reportgrowth.workflowinflectlm_parmslm_windowlow.integrateparse_dataparse_Gen5Gen6parse_victornivoparse_victorx3plot.dr_parameterplot.drBootSplineplot.drFitplot.drFitflplot.drFitFLModelplot.drFitModelplot.drFitSplineplot.dualplot.flBootSplineplot.flFitplot.flFitLinearplot.flFitResplot.flFitSplineplot.gcBootSplineplot.gcFitLinearplot.gcFitModelplot.gcFitSplineplot.gridplot.grodataplot.grofitplot.parameterrdm.dataread_dataread_filerun_apptable_group_fluorescence_lineartable_group_fluorescence_splinetable_group_growth_lineartable_group_growth_modeltable_group_growth_splinetidy_to_customzipFastener

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacellrangerclicodetoolscolorspacecommonmarkcorrplotcowplotcpp11crayoncrosstalkDerivdigestdoBydoParalleldplyrdrcDTevaluatefansifarverfastmapfontawesomeforeachFormulafsgenericsggh4xggnewscaleggplot2ggpubrggrepelggsciggsignifgluegridExtragtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvisobanditeratorsjquerylibjsonlitekableExtraknitrlabelinglaterlatticelazyevallifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminpack.lmminqamodelrmultcompmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplotrixplyrpolynomprettyunitsprogresspromisespurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreadxlrematchrlangrmarkdownrstatixrstudioapisandwichsassscalesshinysourcetoolsSparseMstringistringrsurvivalsvglitesystemfontsTH.datatibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxml2xtableyamlzoo

Q&A and Troubleshooting

Nicolas T. Wirth

Rendered fromtroubleshooting.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-01-26
Started: 2023-04-04

Quantitiative Fluorescence Curve Evaluation with Package QurvE

Nicolas T. Wirth

Rendered fromvignette_fluorescence.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-07-03
Started: 2022-12-19

Quantitiative Growth Curve Evaluation with Package QurvE

Nicolas T. Wirth

Rendered fromvignette_growth.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-01-26
Started: 2022-10-28

QurvE App User Manual v.1.1

Nicolas T. Wirth and Stefano Donati

Rendered fromshiny_app_manual.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-01-26
Started: 2022-12-21

Readme and manuals

Help Manual

Help pageTopics
Internal function used to fit a biosensor response model with 'nlsLM'biosensor.eq
Export an R object as .RData fileexport_RData
Export a tabular object as tab-separated .txt fileexport_Table
Create a 'fl.control' object.fl.control
Fit a biosensor model (Meyer et al., 2019) to response vs. concentration datafl.drFit
Perform a biosensor model fit on response vs. concentration data of a single sample.fl.drFitModel
Create a PDF and HTML report with results from a fluorescence analysis workflowfl.report
Run a complete fluorescence curve analysis and dose-reponse analysis workflow.fl.workflow
flBootSpline: Function to generate a bootstrapflBootSpline
Perform a fluorescence curve analysis on all samples in the provided dataset.flFit
Data fit via a heuristic linear methodflFitLinear
Perform a smooth spline fit on fluorescence dataflFitSpline
Create a 'grofit.control' object.growth.control
Perform a smooth spline fit on response vs. concentration data of a single samplegrowth.drBootSpline
Perform a dose-response analysis on response vs. concentration datagrowth.drFit
Fit various models to response vs. concentration data of a single sample to determine the EC50.growth.drFitModel
Perform a smooth spline fit on response vs. concentration data of a single sample to determine the EC50.growth.drFitSpline
Perform a bootstrap on growth vs. time data followed by spline fits for each resamplegrowth.gcBootSpline
Perform a growth curve analysis on all samples in the provided dataset.growth.gcFit
Fit an exponential growth model with a heuristic linear methodgrowth.gcFitLinear
Fit nonlinear growth models to growth datagrowth.gcFitModel
Perform a smooth spline fit on growth datagrowth.gcFitSpline
Create a PDF and HTML report with results from a growth curve analysis workflowgrowth.report
Run a complete growth curve analysis and dose-reponse analysis workflow.growth.workflow
Find indices of maxima an minima in a data seriesinflect
Helper functions for handling linear fits.lm_parms lm_window
Function to estimate the area under a curve given as x and y(x) valueslow.integrate
Parse raw plate reader data and convert it to a format compatible with QurvEparse_data
Extract relevant data from a raw data export file generated with the "Gen5" or "Gen6" software.parse_Gen5Gen6
Extract relevant data from a raw data export file generated from the software of Perkin Elmer's "Victor Nivo" plate readers.parse_victornivo
Extract relevant data from a raw data export file generated from the software of Perkin Elmer's "Victor X3" plate readers.parse_victorx3
Compare calculated dose-response parameters between conditions.plot.dr_parameter
Generic plot function for 'gcBootSpline' objects.plot.drBootSpline
Generic plot function for 'drFit' objects.plot.drFit
Generic plot function for 'drFitFL' objects.plot.drFitfl
Generic plot function for 'drFitFLModel' objects.plot.drFitFLModel
Generic plot function for 'drFitModel' objects.plot.drFitModel
Generic plot function for 'drFitSpline' objects.plot.drFitSpline
Compare fluorescence and growth over timeplot.dual
Generic plot function for 'flBootSpline' objects.plot.flBootSpline
Generic plot function for 'flcFittedLinear' objects. Plot the results of a linear regression on ln-transformed dataplot.flFitLinear
Combine different groups of samples into a single plotplot.flFit plot.flFitRes
Generic plot function for 'flFitSpline' objects.plot.flFitSpline
Generic plot function for 'gcBootSpline' objects.plot.gcBootSpline
Generic plot function for 'gcFittedLinear' objects. Plot the results of a linear regression on ln-transformed dataplot.gcFitLinear
Generic plot function for 'gcFitModel' objects.plot.gcFitModel
Generic plot function for 'gcFitSpline' objects.plot.gcFitSpline
Plot a matrix of growth curve panelsplot.grid
Generic plot function for 'grodata' objects. Plots raw growth, fluorescence, or normalized fluorescence data of multiple samples or conditions.plot.grodata
Generic plot function for 'grofit' objects. Combine different groups of samples into a single plotplot.grofit
Compare growth parameters between samples or conditionsplot.parameter
The function calls the 'baranyi' function to generate curves between time zero and 't' and adds some random noise to the x- and y-axes. The three growth parameters given as input values will be slightly changed to produce different growth curves. The resulting datasets can be used to test the 'growth.workflow' function.rdm.data
Read growth and fluorescence data in table formatread_data
Call the appropriate function required to read a table file and return the table as a dataframe object.read_file
Run Shiny QurvE Apprun_app
Generic summary function for drBootSpline objectssummary.drBootSpline
Generic summary function for drFit objectssummary.drFit
Generic summary function for drFitfl objectssummary.drFitfl
Generic summary function for drFitFLModel objectssummary.drFitFLModel
Generic summary function for drFitModel objectssummary.drFitModel
Generic summary function for drFitSpline objectssummary.drFitSpline
Generic summary function for flBootSpline objectssummary.flBootSpline
Generic summary function for flFit objectssummary.flFit
Generic summary function for flFitLinear objectssummary.flFitLinear
Generic summary function for flFitSpline objectssummary.flFitSpline
Generic summary function for gcBootSpline objectssummary.gcBootSpline
Generic summary function for gcFit objectssummary.gcFit
Generic summary function for gcFitLinear objectssummary.gcFitLinear
Generic summary function for gcFitModel objectssummary.gcFitModel
Generic summary function for gcFitSpline objectssummary.gcFitSpline
Generate a grouped results table for linear fits with average and standard deviationstable_group_fluorescence_linear
Generate a grouped results table for spline fits with average and standard deviationstable_group_fluorescence_spline
Generate a grouped results table for linear fits with average and standard deviationstable_group_growth_linear
Generate a grouped results table for parametric fits with average and standard deviationstable_group_growth_model
Generate a grouped results table for spline fits with average and standard deviationstable_group_growth_spline
Combine two dataframes like a zip-fastenerzipFastener